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Spatial and cell type specific molecular genetic investigations of inflammatory myopathies with selective perifascicular injury [RNA]

GSE331197 Homo sapiens (human) RNA-seq (gene expression) 300 samples Submitted 2026/07/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 300 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
300 samples: 27 conditions, mostly with about 12 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Lupus myositis, a type I interferon driven necrotizing myopathy with regional heterogeneityResearch square · 2026
Summary (written by the submitters)
Idiopathic inflammatory myopathies (IIM) are a heterogeneous group of systemic autoimmune disease often with multisystem involvement. Targeted therapy is still lacking. Efficient serum or histological markers to measure disease activity and predict disease course are missing. Perifascicular myofiber atrophy is a hall mark of dermatomyositis (DM).
Read the full summary ↓
Despite decades of research, the mechanism of perifascicular atrophy is still incompletely understood. Across other IIM subtypes, perifascicular myofiber necrosis is also the hall mark pathology for antisynthetase syndrome associated myositis (ASyS)5, and can be seen in a subset of lupus myositis (LM). We hypothesize that direct comparison between tissue within the diseased perifascicular regions (PF) and the relatively normal centro-fascicular (CF) regions will help narrow down tissue specific drivers underlying the muscle injury (necrosis versus atrophy) in a disease specific manner.
Published in
Lupus myositis, a type I interferon driven necrotizing myopathy with regional heterogeneity
Beechar A, Bermas B, Zhu C et al. · Research square 2026 · PMID 42427858 · doi:10.21203/rs.3.rs-10072964/v1
This dataset
Open GSE331197 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE331197_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1467468 and SRA study SRP701531. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42427858) ↗
Study design
27 conditions, mostly with about 12 replicates each
DSP-1001660014456-E-B ×12 DSP-1001660014456-E-C ×12 DSP-1001660014456-E-D ×12 DSP-1001660014603-D-B ×12 DSP-1001660014603-D-C ×12 DSP-1001660014603-D-D ×12 DSP-1001660014603-D-E ×12 DSP-1001660014603-D-G ×12 +19 more

Supports a between-group comparison across 300 samples.

How we read this: 27 replicated groups read from 300 sample titles; they account for 300 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 260 more — browse all 300 samples with per-sample file links →

Datasets on a similar topic

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